Search Results for author:
Found 8 papers, 5 papers with code
Return Dispersion as an Estimator of Learning Potential for Prioritized Level Replay
Prioritized Level Replay (PLR) has been shown to induce adaptive curricula that improve the sample-efficiency and generalization of reinforcement learning policies in environments featuring multiple tasks or levels.
A Closer Look at the Adversarial Robustness of Information Bottleneck Models
We study the adversarial robustness of information bottleneck models for classification.
Exchangeable Models in Meta Reinforcement Learning
One recent approach to meta reinforcement learning (meta-RL) is to integrate models for task inference with models for control.
Discriminative Topic Modeling with Logistic LDA
We propose logistic LDA, a novel discriminative variant of latent Dirichlet allocation which is easy to apply to arbitrary inputs.
BRUNO: A Deep Recurrent Model for Exchangeable Data
We present a novel model architecture which leverages deep learning tools to perform exact Bayesian inference on sets of high dimensional, complex observations.
Faster gaze prediction with dense networks and Fisher pruning
Predicting human fixations from images has recently seen large improvements by leveraging deep representations which were pretrained for object recognition.
Fast Face-swap Using Convolutional Neural Networks
We consider the problem of face swapping in images, where an input identity is transformed into a target identity while preserving pose, facial expression, and lighting.
Music transcription modelling and composition using deep learning
We apply deep learning methods, specifically long short-term memory (LSTM) networks, to music transcription modelling and composition.
